This research introduces a scalable Anomaly Detection Service with a generalizable API designed specifically for industrial time-series data in cloud environments.

• Leverages Large Language Models to understand and interpret complex cloud infrastructure anomalies
• Provides proactive identification of potential issues before they impact system performance
• Offers a generalizable API that can be integrated across diverse cloud monitoring systems
• Enhances operational efficiency for Site Reliability Engineers managing large-scale cloud deployments

For Engineering teams, this innovation significantly improves cloud infrastructure resilience by combining advanced ML techniques with domain-specific knowledge, reducing downtime and accelerating issue resolution.

LLM Assisted Anomaly Detection Service for Site Reliability Engineers: Enhancing Cloud Infrastructure Resilience